Classes |
| class | ConvergenceCriteria |
| | ConvergenceCriteria represents an abstract base class for different convergence criteria used in registration loops. More...
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| class | CorrespondenceEstimation |
| | CorrespondenceEstimation represents the base class for determining correspondences between target and query point sets/features. More...
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| class | CorrespondenceEstimationBackProjection |
| | CorrespondenceEstimationBackprojection computes correspondences as points in the target cloud which have minimum More...
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| class | CorrespondenceEstimationBase |
| | Abstract CorrespondenceEstimationBase class. All correspondence estimation methods should inherit from this. More...
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| class | CorrespondenceEstimationNormalShooting |
| | CorrespondenceEstimationNormalShooting computes correspondences as points in the target cloud which have minimum distance to normals computed on the input cloud More...
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| class | CorrespondenceEstimationOrganizedProjection |
| | CorrespondenceEstimationOrganizedProjection computes correspondences by projecting the source point cloud onto the target point cloud using the camera intrinsic and extrinsic parameters. The correspondences can be trimmed by a depth threshold and by a distance threshold. It is not as precise as a nearest neighbor search, but it is much faster, as it avoids the usage of any additional structures (i.e., kd-trees). More...
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| class | CorrespondenceRejectionOrganizedBoundary |
| | The CorrespondenceRejectionOrganizedBoundary class implements a simple correspondence rejection measure. For each pair of points in correspondence, it checks whether they are on the boundary of a silhouette. This is done by counting the number of NaN dexels in a window around the points (the threshold and window size can be set by the user). More...
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| class | CorrespondenceRejector |
| class | CorrespondenceRejectorDistance |
| class | CorrespondenceRejectorFeatures |
| | CorrespondenceRejectorFeatures implements a correspondence rejection method based on a set of feature descriptors. Given an input feature space, the method checks if each feature in the source cloud has a correspondence in the target cloud, either by checking the first K (given) point correspondences, or by defining a tolerance threshold via a radius in feature space. More...
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| class | CorrespondenceRejectorMedianDistance |
| | CorrespondenceRejectorMedianDistance implements a simple correspondence rejection method based on thresholding based on the median distance between the correspondences. More...
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| class | CorrespondenceRejectorOneToOne |
| | CorrespondenceRejectorOneToOne implements a correspondence rejection method based on eliminating duplicate match indices in the correspondences. Correspondences with the same match index are removed and only the one with smallest distance between query and match are kept. That is, considering match->query 1-m correspondences are removed leaving only 1-1 correspondences. More...
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| class | CorrespondenceRejectorPoly |
| | CorrespondenceRejectorPoly implements a correspondence rejection method that exploits low-level and pose-invariant geometric constraints between two point sets by forming virtual polygons of a user-specifiable cardinality on each model using the input correspondences. These polygons are then checked in a pose-invariant manner (i.e. the side lengths must be approximately equal), and rejection is performed by thresholding these edge lengths. More...
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| class | CorrespondenceRejectorSampleConsensus |
| | CorrespondenceRejectorSampleConsensus implements a correspondence rejection using Random Sample Consensus to identify inliers (and reject outliers) More...
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| class | CorrespondenceRejectorSampleConsensus2D |
| | CorrespondenceRejectorSampleConsensus2D implements a pixel-based correspondence rejection using Random Sample Consensus to identify inliers (and reject outliers) More...
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| class | CorrespondenceRejectorSurfaceNormal |
| class | CorrespondenceRejectorTrimmed |
| | CorrespondenceRejectorTrimmed implements a correspondence rejection for ICP-like registration algorithms that uses only the best 'k' correspondences where 'k' is some estimate of the overlap between the two point clouds being registered. More...
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| class | CorrespondenceRejectorVarTrimmed |
| class | DataContainer |
| class | DataContainerInterface |
| class | DefaultConvergenceCriteria |
| | DefaultConvergenceCriteria represents an instantiation of ConvergenceCriteria, and implements the following criteria for registration loop evaluation: More...
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| class | ELCH |
| | ELCH (Explicit Loop Closing Heuristic) class More...
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| class | GraphHandler |
| | GraphHandler class is a wrapper for a general SLAM graph The actual graph class must fulfil the following boost::graph concepts: More...
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| class | GraphOptimizer |
| | GraphOptimizer class; derive and specialize for each graph type More...
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| class | LUM |
| | Globally Consistent Scan Matching based on an algorithm by Lu and Milios. More...
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| struct | NullEstimate |
| | NullEstimate struct More...
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| struct | NullMeasurement |
| | NullMeasurement struct More...
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| struct | PoseEstimate |
| | PoseEstimate struct More...
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| struct | PoseMeasurement |
| | PoseMeasurement struct More...
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| struct | sortCorrespondencesByDistance |
| struct | sortCorrespondencesByMatchIndex |
| struct | sortCorrespondencesByMatchIndexAndDistance |
| struct | sortCorrespondencesByQueryIndex |
| struct | sortCorrespondencesByQueryIndexAndDistance |
| class | TransformationEstimation |
| | TransformationEstimation represents the base class for methods for transformation estimation based on: More...
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| class | TransformationEstimation2D |
| class | TransformationEstimationLM |
| class | TransformationEstimationPointToPlane |
| class | TransformationEstimationPointToPlaneLLS |
| | TransformationEstimationPointToPlaneLLS implements a Linear Least Squares (LLS) approximation for minimizing the point-to-plane distance between two clouds of corresponding points with normals. More...
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| class | TransformationEstimationPointToPlaneLLSWeighted |
| | TransformationEstimationPointToPlaneLLSWeighted implements a Linear Least Squares (LLS) approximation for minimizing the point-to-plane distance between two clouds of corresponding points with normals, with the possibility of assigning weights to the correspondences. More...
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| class | TransformationEstimationPointToPlaneWeighted |
| class | TransformationEstimationSVD |
| class | TransformationEstimationSVDScale |
| class | TransformationValidation |
| | TransformationValidation represents the base class for methods that validate the correctness of a transformation found through TransformationEstimation. More...
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| class | TransformationValidationEuclidean |
| | TransformationValidationEuclidean computes an L2SQR norm between a source and target dataset. More...
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| class | WarpPointRigid |
| | Base warp point class. More...
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| class | WarpPointRigid3D |
| | WarpPointRigid3D enables 3D (1D rotation + 2D translation) transformations for points. More...
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| class | WarpPointRigid6D |
| | WarpPointRigid3D enables 6D (3D rotation + 3D translation) transformations for points. More...
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Functions |
| void | getCorDistMeanStd (const pcl::Correspondences &correspondences, double &mean, double &stddev) |
| | calculates the mean and standard deviation of descriptor distances from correspondences
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| void | getMatchIndices (const pcl::Correspondences &correspondences, std::vector< int > &indices) |
| | extracts the match indices
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| void | getQueryIndices (const pcl::Correspondences &correspondences, std::vector< int > &indices) |
| | extracts the query indices
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